[mccall.278]

Reena- Hi Reena, thanks for sharing your thoughts! I do agree with your statement on how big of an impact this will have on our nursing careers. We should be part of the implementation process, if this is where the future of healthcare is going. With that being said, I believe that they will need to provide nurses with additional training, so we can use AI correctly and not cause patient harm.

Kathy – Hi Kathy, thanks for sharing your thoughts! I do agree with your statement that AI could benefit nursing from a staffing standpoint. We are consistently facing issues with being short-staffed. If AI could help staffing issues in any way, but still provide the utmost care for our patients, I do not see an issue with AI.

[junge.23]

Hi Greg!
I never heard the term GIGO before, but it is spot on with AI. AI’s only as smart as the data it learns from, and if that data’s flawed or outdated, the results can be way off, misleading, and affect patient outcomes. I feel that unless we’re constantly updating and retraining AI with the latest, most accurate data, it’ll keep making decisions based on stuff that might no longer be true. Realistically, replacing and updating all the medical data AI relies on sounds incredibly time-consuming.

Hi Brandi!
Thanks for participating! You bring up some very valid questions about the current practice. There’s a lot to think about—like whether patients will see AI-generated suggestions, and whether we’ll have to defend our decisions against them. Nurses will definitely need training not just to use AI, but to critically evaluate it. We will have to know when to trust the tool and when to trust ourselves.

[conrad.369]

Hello! My name is Katie Conrad and I am a nurse from OP JCRU. AI in healthcare is an interesting topic that I am glad we are discussing.

1. What was the knowledge gained from the article?
Both articles made it clear that AI is already changing how nurses work, not something that’s just coming “someday.” Billingsley et al. (2024) talked about how AI can make health care more efficient and improve patient outcomes, but they also pointed out that we have to be really careful with how we handle patient data and make sure we’re thinking about ethics. It’s not just about using new tech — it’s about using it responsibly.
Gallegos (2023) focused more on urologic nursing and gave examples of how AI is helping with things like diagnostics and saving time. They stressed that nurses need to keep learning and stay flexible because the technology is moving fast.
2. What other questions does the article raise about current practice?
Both articles raise some big questions about how ready we actually are for AI in nursing. Billingsley et al. (2024) made me wonder: are our current policies strong enough to protect patient data when AI systems are involved? They also made me think about whether nurses are getting enough training to recognize bias in AI tools — and what happens if we start trusting technology too much and lose some of our critical thinking skills.
Gallegos (2023) raised the question of whether nurses in specialty areas like urology are really prepared to use AI tools day-to-day. Are we getting the right education and support to use these tools effectively without losing the personal connection we have with patients? And how do we make sure AI helps nurses rather than just adding another layer of complexity?
3. Do you agree/disagree with the conclusions of the author, why?
I do agree that nursing needs to be involved with AI and how nursing care will evolve regarding AI. I also agree that AI has some concerns as well. These concerns arise when ethical concerns like algorithm bias and fairness comes to mind. Gallegos (2023) article shows that AI can improve diagnostic accuracy, assist in treatment planning, and save time on repetitive tasks, freeing up nurses to spend more time with their patients. However, Gallegos also points out that the fast pace of AI development means nurses must stay proactive about learning new systems and skills to keep up. There’s a concern that without enough training and support, technology could create more stress instead of reducing it. I am all for efficiency that the articles mention but worried at what cost are we trading efficiency for.

[conrad.369]

Jennifer-

I couldn’t help but think about an AI situation regarding EKGs. The information I was reading an article that discussed that AI can start to interpret EKGs so accurately that they can identify if the patient is male or female. This is leading to a more detailed report and the ability to determine disease processes in females vs males. Knowing the CTU uses EKGs so frequently, I wonder if that could be another tool to help learn even more about the trial.

Brandi-

It is very interesting thinking about what liability nurses assume with AI generated care. One would hope that more standardize care will result in better outcomes for patients.

[conrad.369]

Kelly- You asked of an example of AI that is used here at OSU. I’m not sure if this is exactly AI but OSU uses data (I feel like the word algorithms are appropriate to use in this situation but not sure) such as rising white blood counts, other labs and current vital signs and a MEWS number is computed. That number is computed in EPIC and alerts nursing staff that the patient has potential to deteriorate. STAT nurses are able change their epic views to specify patients with high MEWS scores. From there they are flagged as someone who needs closer observations and or interventions.

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